The invention relates to online content analysis, and in particular to hot video prediction systems and methods based on a user's social network.
This section is intended to introduce the reader to various aspects of the art, which may be related to various aspects of the present invention, which are described and/or claimed below. This discussion is believed to be helpful in providing the reader with background information to facilitate a better understanding of the various aspects of the present invention. Accordingly, it should be understood that these statements are to be read given said understanding, and not as admissions of prior art.
Conventionally, predicting popular content, such as online news and blogs, is performed by calculating similarity of context vectors to cluster contents corresponding to similar topics.
The conventional method, however, cannot effectively analyze video data which is constantly being updated and lacks context contents. Thus, it is difficult to predict hot videos by clustering videos based on context. First, context is not always contained in a video. Second, popularity of videos corresponding to the same theme might be completely different.
Accordingly, an effective hot video prediction method is needed.